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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Application of MODIS Products to Infer Possible Relationships Between Basin Land Cover and Coastal Waters Turbidity Using the Magdalena River, Colombia, as a Case Study

Basin development and consequent change in basin land cover have been often associated with an increased turbidity in coastal waters because of sediment yield and nutrients loading. The later leads to phytoplankton abundance further exacerbating water turbidity. This subsequently affects biological and physical processes in coastal estuaries by interfering with sun light penetration to coral reefs and sea grass, and even affecting public health. Therefore, consistent estimation of land cover changes and turbidity trend lines is crucial to design environmental and restoration management plans, to predict fate of possible pollutants, and to estimate sedimentary fluxes into the ocean. Ground solely methods to estimate land cover change would be unpractical and traditional methods of monitoring in situ water turbidity can be very expensive and time consuming. Accurate monitoring on the status and trends of basin land cover as well as the water quality of the receiving water bodies are required for analysis of relationships between the two variables. Use of remote sensing (RS) technology provides a great benefit for both fields of study, facilitating monitoring of changes in a timely and cost effective manner and covering wide areas with long term measurements. In this study, the Magdalena River basin and fixed geographical locations in the estuarine waters of its delta are used as a case to study the temporal trend lines of both, land cover change and the reflectance of the water turbidity using satellite technology. Land cover data from a combined product between sensors Terra and Aqua (MCD12Q1) from MODIS will be adapted to the conditions in the Magdalena basin to estimate changes in land cover since year 2000 to 2009. Surface reflectance data from a MODIS, Terra (MOD09GQ), band 1, will be used in lieu of in situ water turbidity for the time period between 2000 and present. Results will be compared with available existing data.

Madrinan, Max Jacobo Moreno↗
NASA NTRS1994

A Study on the Effect of Communication Performance on Message-Passing Parallel Programs: Methodology and Case Studies

From a source-program perspective, the performance achieved on distributed/parallel systems is governed by the underlying message-passing library overhead and the network capabilities of the architecture. Studying the impact of changes in these features on the source-program. can have a significant influence in the development of next-generation system designs. In this paper we introduce a simple and robust tool that can be used for this purpose. This tool is based on event-driven simulation of programs that generates a new set of trace events - that preserves causality and partial order - corresponding to the expected execution of the program in the simulated environment. Trace events can be visualized and source-level profile information can be used to pin-point locations of program which are most significantly affected with changing system parameters in the simulated environment. We present a number of examples from the NAS benchmark suite, executed on the Intel Paragon and iPSC/860 that are used to identify and expose performance bottlenecks with varying system parameters. Specific aspects of the system that significantly effect these benchmarks are presented and discussed,

Sarukkai, Sekhar R.↗
DOE OSTI2020

Environmental and Economic Assessments and Uncertainties of Multiple Lignocellulosic Biomass Utilization for Bioenergy Products: Case Studies

Life-cycle assessment (LCA) and techno-economic analysis (TEA) were applied to assess the economic feasibility and environmental benefits of utilizing multiple biomass feedstocks for bioenergy products under three different technological pathways with consideration of uncertainties. Three cases were studied for the production of pellets, biomass-based electricity, and pyrolysis bio-oil. A Monte Carlo simulation was used to examine the uncertainties of fossil energy consumption, bioenergy conversion efficiency, stochastic production rate, etc. The cradle-to-gate LCA results showed that pellet production had the lowest greenhouse gas (GHG) emissions, water and fossil fuels consumption (8.29 kg CO2 eq (equivalent), 0.46 kg, and 105.42 MJ, respectively). The conversion process presented a greater environmental impact for all three bioenergy products. When producing 46,929 Mg of pellets, 223,380 MWh of electricity, and 78,000 barrels of pyrolysis oil, the net present values (NPV) indicated that only pellet and electricity production were profitable with NPVs of $1.20 million for pellets, and $5.59 million for biopower. Uncertainty analysis indicated that pellet production showed the highest uncertainty in GHG emission, and bio-oil production had the least uncertainty in GHG emission but had risks producing greater-than-normal amounts of GHG. Biopower production had the highest probability to be a profitable investment with 85.23%.

09 BIOMASS FUELS↗
NASA NTRS2000

Vibroacoustic Response of Solar Panels: Case Study

Large surface area, lightweight structures, such as solar panels, are easily excited by sound and often experience high acceleration responses during acoustic tests.

SEA vibroacoustics VAPEPS case study D-11341↗
DOE OSTI2025

A Comparative Study of Physics‐Informed and Data‐Driven Neural Networks for Compound Flood Simulation at River‐Ocean Interfaces: A Case Study of Hurricane Irene

Simulating compound flooding (CF) at the river-ocean interface within large-scale Earth System Models (ESMs) presents significant challenges due to complex interactions between river discharge, storm surge, and tides. This study assesses the comparative advantages of physics-informed and data-driven machine learning (ML) approaches for enhancing local ESM performance. We systematically compare data-driven neural network models (i.e., CNNs, U-Net, Long Short-Term Memory (LSTM), Gated Recurrent Unit), and physics-informed neural network (PINN) models, including vanilla PINN and a finite-difference-based PINN (FD-PINN). Specifically, FD-PINN is introduced to enhance computational efficiency, accelerating vanilla PINNs by ∼6.5 times while improving accuracy. To enhance data-driven model training, a new data-generation approach is developed to sample historical fluvial and coastal flood events, which ensures a robust data set for extreme event prediction. The models are evaluated using a realistic one-dimensional river domain extracted from an ESM's river mesh and the Hurricane Irene event as an independent test case. Results show that FD-PINN achieves accurate predictions with significantly reduced computational costs relative to vanilla PINNs. Among data-driven models, the best overall performance is achieved by a CNN-LSTM hybrid, which balances accuracy and efficiency. While a fully connected CNN (CNN-FC) provides the best accuracy, it incurs high computational cost. Architectures lacking strong temporal modeling tend to underperform on unseen events. These findings highlight the importance of sequence-aware designs for robust generalization. This study reveals the trade-offs between physics-informed and data-driven models and proposes an adaptive hybrid framework for integrating ML into ESMs to enhance local flood simulations.

Earth Systems Modeling↗
DOE OSTI2022

Carbon footprint prediction considering the evolution of alternative fuels and cargo: A case study of Yangtze river ships

For reducing carbon emissions in the shipping sector, application of alternative low-carbon and zero-carbon fuels is the consensus. However, requirements of economic development cannot be ignored while focusing on emission reduction. Cargo development is an important prerequisite. Considering the cargo growth as a novelty, a method to calculate the annual carbon emissions of different alternative fuel-powered ships in different cargo growth prospects and power scenarios is proposed. With respect to the time dimension, the relationship between alternative fuels, cargo, and carbon reduction is revealed. The Yangtze River bulk carrier case was studied and the life cycle carbon emission analysis of diesel, LNG hybrid, LNG, hydrogen, methanol, and ammonia were carried out. The annual carbon curves of the high, steady, and low cargo growth prospects were obtained for different scenarios of the power system structure. The results show that LNG hybrid, LNG and methanol fuels are currently the suitable choices. Their life cycle carbon emissions were reduced by 31.5–38.1% compared with those of diesel power. The carbon emissions of green hydrogen and green ammonia were reduced by 78.8% and 91.3%, respectively, compared with those of hydrogen and ammonia. The carbon reduction results of green fuels in their initial application were explored which are at 0.6–10.8%. In addition, there is a balanced annual growth rate, whose annual carbon curve will be steady under its corresponding scenario of power system structure, which could help the ship owners plan their future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1982

A preliminary study of the application of HCMM satellite data to define initial and boundary conditions for numerical models: A case study in St. Louis, Missouri

Infrared and visible HCMM data were used to examine the potential application of these data to define initial and boundary conditions for mesoscale numerical models. Various boundary layer models were used to calculate the distribution of the surface heat flux, specific humidity depression (the difference between the specific humidity in the air at approxmately the 10 m level and the specific humidity at the ground), and the eddy vicosity in a 72 km by 72 km area centered about St. Louis, Missouri. Various aspects of the implications of the results on the meteorology of St. Louis are discussed. Overall, the results indicated that a reasonable estimate of the surface heat flux, urban albedo, ground temperature, and specific humidity depression can be obtained using HCMM satellite data. Values of the ground-specific humidity can be obtained if the distribution of the air-specific humidity is available. More research is required in estimating the absolute magnitude of the specific humidity depression because calculations may be sensitive to model parameters.

Vukovich, F. M.↗
DOE OSTI2026

Case Study: BESS Capacity Building for Malawi

To strengthen Malawi's national electricity grid and to enhance reliability, the government of Malawi and the Electricity Supply Corporation of Malawi are partnering with the Global Alliance for People and Planet to develop a 20-megawatt/30-megawatt-hour battery energy storage system at Kanengo, Malawi, expected to come online in 2026. In parallel, the Global Energy Alliance for People and Planet and the National Laboratory of the Rockies implemented a comprehensive technical capacity-building program to equip the Electricity Supply Corporation of Malawi, the Malawi Energy Regulatory Authority, and the Malawi University of Business and Applied Sciences with the expertise needed to plan, regulate, and operate advanced storage systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Reservoir Dynamics in Proposed Operational Scenarios Where CO 2 -EOR Fields are Transitioned From CO 2 -Flood Enhanced Oil Recovery to Dedicated Carbon Storage: A Field Case Study

This study models the transition of CO 2 -enhanced oil recovery (CO 2 -EOR) fields to dedicated carbon storage using a generalized reservoir model informed by real field data, SACROC. Through scenario-based simulations, the work evaluates how reservoir depletion levels, boundary conditions, fluid properties, and domain size affect pressure buildup, CO 2 plume migration, and long-term containment performance. The results inform practices for repurposing oil fields into reliable CO 2 storage sites.

02 PETROLEUM↗
DOE OSTI2020

Connecting Risk and Resilience for a Power System Using the Portland Hills Fault Case Study

Active seismic faults in the Pacific Northwest area have encouraged electric utilities in the region to deeply contemplate and proactively intervene to support grid resilience. To further this effort this research introduces Monte Carlo (MC)-based power system modeling as a means to inform the Performance Based Earthquake Engineering method and simulates 100,000 sample earthquakes of a 6.8 magnitude (M6.8) Portland Hills Fault (PHF) scenario in the Portland General Electric (PGE) service territory as a proof of concept. This paper also proposes the resilience metric Seismic Load Recovery Factor (SLRF) to quantify the recovery of a downed power system and thus can be used to quantify earthquake economic risk. Using MC results, the SLRF was evaluated to be 19.7 h and the expected economic consequence cost of a M6.8 PHF event was found to be $\$180$ million with an annualized risk of $\$90,000$ given the event’s 1 in 2000 year probability of occurrence. The MC results also identified the eight most consequential substations in the PGE system—i.e., those that contributed to maximum load loss. This paper concludes that retrofitting these substations reduced the expected consequence cost of a M6.8 PHF event to $117 million.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2023

The Impact (Influence) of Stakeholder Participation in the Logic Modeling Process: A Case Study from NASA Goddard Space Flight Center

This is a three-paper dissertation that responds to a call for empirical research on stakeholder influence in the implementation of evaluation recommendations. The literature is consistent but mostly theoretical: stakeholder participation should positively influence and increase the probability of implementation (see e.g., Christie, 2011; Cousins and Earl, 1992); Fetterman, 2004). In response, I use two Goddard Space Flight Center engineering technical training and development programs to build a causal pathway argument supporting my proposition that stakeholder influence in the logic modeling process impacts organizational decision-making and change. I first introduce the logic modeling process as a tool to involve stakeholders in program and evaluation design (paper 1), then use the data collection process to implement the collaboratively constructed logic model outcomes (paper 2), and finally, I triangulate the data using the Toal (2009) Evaluation Involvement Scale (paper 3). I do this to “increase the validity of the findings” (Noble & Heale, 2019, p. 67) and to garner potential mechanisms. I found that stakeholder participation in the logic modeling process positively influenced the use of data to inform recommendations which in turn positively influenced implementation of evaluation recommendations. I identified the process itself as the mechanism and the key decision points as links or influencers. Potential factors included power and interest (measured by role) and time-on-job.

Organizational Decision-Making↗
DOE OSTI2024

A Mobility Energy Productivity Evaluation of On-Demand Transit: A Case Study in Arlington, Texas

On-demand transit (ODT) systems are increasing in number and size. In order to evaluate and quantify outcomes, we use the Mobility Energy Productivity (MEP) metric, a holistic tool to analyze, quantify, and compare the mobility and accessibility of various transportation modes in a specific area. In this paper, we apply the MEP tool to the ODT system in Arlington, Texas, and compare the results among four existing transportation modes (drive, transportation network company, transit, and bike) and five additional ODT scenarios. We focus our analysis on the opportunities that an ODT system presents such as serving disadvantages communities. While the results in Arlington show the typical U.S. pattern of driving receiving the highest MEP score, the ODT system best serves those in disadvantaged communities, helping with an equity design goal. ODT improved the average MEP score across the service area by 100% when considering only non-private vehicle modes (bike, transit, and ODT). For the ODT scenarios, decreasing the wait time 50% compared to the baseline scenario led to a nearly 160% increase in MEP score, while increasing the ODT travel speed by 21% led to an 80% improvement in MEP score. The decreased wait time scenario had the highest MEP score out of the six ODT scenarios. This paper demonstrates how ODT can enhance mobility, particularly for disadvantaged communities. The results of a MEP analysis can be used by researchers and transit agencies to compare transportation modes and improve the effectiveness of transportation systems in subareas across a service area.

accessibility↗
NASA NTRS2004

A Case Study of the Impact of AIRS Temperature Retrievals on Numerical Weather Prediction

Large errors in numerical weather prediction are often associated with explosive cyclogenesis. Most studes focus on the under-forecasting error, i.e. cases of rapidly developing cyclones which are poorly predicted in numerical models. However, the over-forecasting error (i.e., to predict an explosively developing cyclone which does not occur in reality) is a very common error that severely impacts the forecasting skill of all models and may also present economic costs if associated with operational forecasting. Unnecessary precautions taken by marine activities can result in severe economic loss. Moreover, frequent occurrence of over-forecasting can undermine the reliance on operational weather forecasting. Therefore, it is important to understand and reduce the prdctions of extreme weather associated with explosive cyclones which do not actually develop. In this study we choose a very prominent case of over-forecasting error in the northwestern Pacific. A 960 hPa cyclone develops in less than 24 hour in the 5-day forecast, with a deepening rate of about 30 hPa in one day. The cyclone is not versed in the analyses and is thus a case of severe over-forecasting. By assimilating AIRS data, the error is largely eliminated. By following the propagation of the anomaly that generates the spurious cyclone, it is found that a small mid-tropospheric geopotential height negative anomaly over the northern part of the Indian subcontinent in the initial conditions, propagates westward, is amplified by orography, and generates a very intense jet streak in the subtropical jet stream, with consequent explosive cyclogenesis over the Pacific. The AIRS assimilation eliminates this anomaly that may have been caused by erroneous upper-air data, and represents the jet stream more correctly. The energy associated with the jet is distributed over a much broader area and as a consequence a multiple, but much more moderate cyclogenesis is observed.

Reale, O.↗
NASA NTRS1994

SAGE 2-Umkehr case study of ozone differences and aerosol effects from October 1984 to April 1989

A comparison of 1262 cases of coincident ozone profiles derived from 666 Umkehrs at 17 different stations and 901 SAGE 2 profiles within 1000 km and 12 hours between October 1984 and April 1989 indicates the following layer percentage differences with 2-sigma error bars: layer three 14.6 plus/minus 3.3 percent, layer four 17.6 plus/minus 1.1 percent, layer five -1.3 plus/minus 0.5 percent, layer six -5.7 plus/minus 0.7 percent, layer seven -1.0 plus/minus 0.7 percent, layer eight 4.2 plus/minus 0.7 percent, and layer nine 6.8 plus/minus 1.2 percent. Comparing SAGE 2-Umkehr differences to SAGE 1 version 5.5-Umkehr differences shows SAGE 2 higher than or equal to SAGE 1 relative to Umkehr in all layers except layer three. Adjustment for this bias would produce trends derived from SAGE 2-SAGE 1 differences and Umkehr observations in the 1980s more nearly equal to each other in layers six, seven, and eight. A possible explanation of these differences is a systematic shift in the reference altitude between SAGE 1 and SAGE 2, but there is no independent evidence of this. While the shape of the vertical profile of differences at 17 individual Umkehr stations (mostly in mid-latitudes) is generally consistent at all stations except at Poker Flat, Seoul, and Lauder, significant variation does exists among the stations. The profile of mean difference is similar to previously observed differences between Umkehr and both SAGE 2 and SBUV and also to an eigenvector analysis, but with site-dependent amplitude discrepancies. Because of the close correspondence of stratospheric aerosol optical depth at the SAGE 2-measured 0.525 micron wavelength and the extrapolated 0.32 Umkehr wavelength determined in this study, we use the 0.525 micron data to determine the aerosol effect of Umkehr profiles. The aerosol errors to the Umkehr ozone amounts in percent ozone amount per 0.01 stratospheric aerosol optical depth range from plus 2 percent in layer six to minus 3 percent in layer nine. These results agree with previous theoretical and empirical studies within their respective error bounds in layers nine, eight, and five. The result in layer six differs significantly from previous works. In view of the fact that SAGE 2 and Umkehr produce different ozone retrievals in layers eight and nine and because the intra-layer correlation of SAGE 2 ozone and aerosol in layers eight and nine in non-zero, one must exercise some caution in attributing the entire SAGE 2-Umkehr differences in the upper layers to an aerosol effect.

Newchurch, M. J.↗
DOE OSTI2023

Porting numerical integration codes from CUDA to oneAPI: a case study

We present our experience in porting optimized CUDA implementations to oneAPI. We focus on the use case of numerical integration, particularly the CUDA implementations of PAGANI and $m$-Cubes. We faced several challenges that caused performance degradation in the oneAPI ports. These include differences in utilized registers per thread, compiler optimizations, and mappings of CUDA library calls to oneAPI equivalents. After addressing those challenges, we tested both the PAGANI and m-Cubes integrators on numerous integrands of various characteristics. To evaluate the quality of the ports, we collected performance metrics of the CUDA and oneAPI implementations on the Nvidia V100 GPU. We found that the oneAPI ports often achieve comparable performance to the CUDA versions, and that they are at most 10% slower.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Impact of boundary layer simulation on predicting radioactive pollutant dispersion: a case study for HANARO Research Reactor using the WRF-MMIF-CALPUFF modeling system

Wind plays an important role in cases of unexpected radioactive pollutant dispersion, deciding distribution and concentration of the leaked substance. The accurate prediction of wind has been challenging in numerical weather prediction models, especially near the surface because of the complex interaction between turbulent flow and topographic effect. As such, in this study, we investigated the characteristics of atmospheric dispersion of radioactive material (i.e. 137 Cs) according to the simulated boundary layer around the HANARO research nuclear reactor in Korea using the Weather Research and Forecasting (WRF)-Mesoscale Model Interface (MMIF)-California Puff (CALPUFF) model system. We examined the impacts of orographic drag on wind field, stability calculation methods, and planetary boundary layer parameterizations on the dispersion of radioactive material under a radioactive leaking scenario. We found that inclusion of the orographic drag effect in the WRF model improved the wind prediction most significantly over the complex terrain area, leading the model system to estimate the radioactive concentration near the reactor more conservatively. We also emphasized the importance of the stability calculation method and employing the skillful boundary layer parameterization to ensure more accurate low atmospheric conditions, in order to simulate more feasible spatial distribution of the radioactive dispersion in leaking scenarios.

54 ENVIRONMENTAL SCIENCES↗